Discrimination of 3 dominant mangrove species from the Pacific coast of Mexico by spectroscopy on intact leaves
Why this work is in the frame
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Bibliographic record
Abstract
Spectral discrimination of mangrove leaves is the first step in classifying remotely sensed imagery of mangrove forests. The objective of this study was to analyze spectroscopic data on leaves from the upper and lower parts of mangrove canopies to discriminate species and physiognomic types. Leaf samples from the upper and lower parts of the canopies of 3 mangrove species (Avicennia germinans, Laguncularia racemosa, and Rhizophora mangle) in 2 physiognomic types (basin and fringe) were collected during 2 seasons (dry and rainy). Probability distribution and first-derivative plots were generated for every wavelength (450–1,000 nm) detected in all samples. With the plots, optimal wavelengths were selected and subsequently verified with a canonical discriminant analysis. Results indicated that all species in basin mangrove forests showed a unique distinction between the upper and lower leaves during the dry season. By contrast, species in fringe mangrove forests did not show this difference during both seasons. Optimal wavelengths for species discrimination were located between 540–560 nm and 700–720 nm, which correspond to the green and red-edge wavebands, respectively. Future studies using remote sensing data with the aforementioned wavebands can be conducted to discriminate physiognomic mangrove forest types and to increase accuracy in the classification of mangroves at the canopy level on the Pacific coast of Mexico.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it